Sensing of parameters can be used to determine information about the environment for many purposes. A sensor can be used to detect conditions which require action. Rapid analysis of this information can enable better and more accurate environmental awareness.
Different ways of obtaining such information are known.
A single point sensor system provides monitoring of only a single location in space. Such devices can be used to detect multiple phenomena in different sensory environments. However, a single point failure mode in these sensors will result in loss of any further data from the environment. Redundant sensors can be provided to avoid this problem, but the redundant sensors typically will not provide additional information, but rather simply act as prevention against failure.
These devices are quite limited in their application. For example, these devices typically do not provide non-local awareness of spatio-temporal phenomena and therefore cannot anticipate or track phenomena, such as a plume moving through the environment.
Airborne and space-based remote sensing systems possess the ability to forecast phenomena through data extrapolation of sensory conditions. This technology however, also has several drawbacks. The existing platforms already have high utilization rates for multiple tasks and the ability to redirect this capability may be limited. In addition, a limitation to the loiter/observation times of airborne and space based platforms exists due to orbital patterns, refueling needs and, in some instances, crew and operator limitations—particularly when observing transient or sporadic phenomena. There are also sensing and sensitivity limitations imposed via physics (i.e. sensing inside building/structures, subterranean, etc.). These systems also prevent raw data from being in the hands of end-users, instead requiring expensive and time-consuming post-data analysis before it is in readable form.
The present system defines use of simple sensor “pods” forming a sensor web. The pods may be heterogeneous or homogeneous. The pods collectively form a sensor web, where even though each individual sensor is extremely simple, the combination/network forms a multi-sensory, trans-environment detection capability with autonomous, reactive capability.
This approach may provide flexibility in adapting the observation and detection capabilities to site-specific needs. It allows for data fusion both locally as with single point sensor methods and over large scales as airborne and space-based methods. The costs and difficulties associated with a complex infrastructure may be minimized by the use of separated nodes, each of which is relatively simple, arranged in a wireless and power-managed web network. The use of the wireless network architecture, embedded in the environment, removes obstacles of single point failure found in single sensor alternatives and of loiter/observation times of space-based alternatives.
In an embodiment, the information can be shared among the Sensor Web pod elements throughout the web. This allows for an adaptive and reactive ability of the network as a whole.
Special aspects of the power management, and especially aspects of the power management which are counter-intuitive, are also described.